“I am here because I wanted to shine”: how poetry can be used to better understand undergraduate students’ first-year chemistry or related course experiences

In this study we investigate how first-year chemistry/biology undergraduate students’ original poetry can be used as a reflective tool for others to understand their course experiences. By inviting students from an integrated first-year chemistry/biology course to write poetry about their experiences, we use poetic content analysis as a qualitative research method to analyze the students’ responses to an open-ended prompt. In analyzing the poetry, four major categories emerged: knowledge, community, emotions, and identity, each of which includes examples that reflect and enhance our understanding of well-documented milestones and ideas in the literature regarding first-year student academic experiences, therefore highlighting the extent to which poetry can be useful in this regard. In presenting these findings we also demonstrate how such an approach might be used by others to better understand student experiences, including those related to learning, belonging, and/or identity in their introductory chemistry or related courses

Resource characteristics and stock assessment of lesser sardines in the Indian waters

The fishery and biology of commercially important species of lesser sardine resources of India were studied. Detailed gearwise, specieswise and monthwise landings for 1984-88 are presented .In Goa-Karnataka region the main gear was purse seine, whereas in the Keralaregion it was gill net. On the east coast, Tamil Nadu- Pondicheny recorded maximum landings through gill nets and Andhra-Orissa through boat seines and gill nets. Surdinellu gibbosa was the imponant species in the west and southeast coasts of India, and S.,fimbriutuin the northeast region. Growth panmeters for different species were estimated. Stock assessment for S. gibbosu showed that the fish is optimally exploited in the Tamil Nadu-Pondicheny region, whereas in the west coast (Kerala and Goa-Kmataka regions) the fishery can be improved with additional effon. In the Andhra-Orissa region. the effon is beyond the MSY level

Question Decomposition Improves the Faithfulness of Model-Generated Reasoning

As large language models (LLMs) perform more difficult tasks, it becomes harder to verify the correctness and safety of their behavior. One approach to help with this issue is to prompt LLMs to externalize their reasoning, e.g., by having them generate step-by-step reasoning as they answer a question (Chain-of-Thought; CoT). The reasoning may enable us to check the process that models use to perform tasks. However, this approach relies on the stated reasoning faithfully reflecting the model's actual reasoning, which is not always the case. To improve over the faithfulness of CoT reasoning, we have models generate reasoning by decomposing questions into subquestions. Decomposition-based methods achieve strong performance on question-answering tasks, sometimes approaching that of CoT while improving the faithfulness of the model's stated reasoning on several recently-proposed metrics. By forcing the model to answer simpler subquestions in separate contexts, we greatly increase the faithfulness of model-generated reasoning over CoT, while still achieving some of the performance gains of CoT. Our results show it is possible to improve the faithfulness of model-generated reasoning; continued improvements may lead to reasoning that enables us to verify the correctness and safety of LLM behavior.Comment: For few-shot examples and prompts, see https://github.com/anthropics/DecompositionFaithfulnessPape

Clinical Outcomes With a Repositionable Self-Expanding Transcatheter Aortic Valve Prosthesis: The International FORWARD Study

Background Clinical outcomes in large patient populations from real-world clinical practice with a next-generation self-expanding transcatheter aortic valve are lacking. Objectives This study sought to document the clinical and device performance outcomes of transcatheter aortic valve replacement (TAVR) with a next-generation, self-expanding transcatheter heart valve (THV) system in patients with severe symptomatic aortic stenosis (AS) in routine clinical practice. Methods The FORWARD (CoreValve Evolut R FORWARD) study is a prospective, single-arm, multinational, multicenter, observational study. An independent clinical events committee adjudicated safety endpoints based on Valve Academic Research Consortium-2 definitions. An independent echocardiographic core laboratory evaluated all echocardiograms. From January 2016 to December 2016, TAVR with the next-generation self-expanding THV was attempted in 1,038 patients with symptomatic, severe AS at 53 centers on 4 continents. Results Mean age was 81.8 ± 6.2 years, 64.9% were women, the mean Society of Thoracic Surgeons Predicted Risk of Mortality was 5.5 ± 4.5%, and 33.9% of patients were deemed frail. The repositioning feature of the THV was applied in 25.8% of patients. A single valve was implanted in the proper anatomic location in 98.9% of patients. The mean aortic valve gradient was 8.5 ± 5.6 mm Hg, and moderate or severe aortic regurgitation was 1.9% at discharge. All-cause mortality was 1.9%, and disabling stroke occurred in 1.8% at 30 days. The expected-to-observed early surgical mortality ratio was 0.35. A pacemaker was implanted in 17.5% of patients. Conclusions TAVR using the next-generation THV is clinically safe and effective for treating older patients with severe AS at increased operative risk. (CoreValve Evolut R FORWARD Study [FORWARD]; NCT02592369

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery